We design the first univariate probability distribution for ordinal data which strictly respects the ordinal nature of data. More precisely, it relies only on order comparisons between modalities. Contrariwise, most competitors either forget the order information or add a nonexistent distance information. The proposed distribution is obtained by modeling the data generating process which is assumed, from optimality arguments, to be a stochastic binary search algorithm in a sorted table. The resulting distribution is natively governed by two meaningful parameters (position and precision) and has very appealing properties: decrease around the mode, shape tuning from uniformity to a Dirac, identifiability. Moreover, it is easily estimated by an EM algorithm since the path in the stochastic binary search algorithm is missing. Using then the classical latent class assumption, the previous univariate ordinal model is straightforwardly extended to modelbased clustering for multivariate ordinal data.
Author  Christophe Biernacki and Julien Jacques 
Date of publication  20160307 15:32:47 
Maintainer  Julien Jacques <julien.jacques@univlyon2.fr> 
License  GPL (>=2) 
Version  1.0 
Package repository  View on RForge 
Installation  Install the latest version of this package by entering the following in R:





All man pages Function index File listing
Man pages  

AERS: French university evaluations  
BOSpackage: ModelBased Clustering of Multivariate Ordinal Data  
clustMultiBOS: Function to cluster multivariate ordinal data 
Functions  

AERS  Man page 
BOS  Man page 
BOSpackage  Man page 
allej  Source code 
clustMultiBOS  Man page Source code 
condprobnolog  Source code 
dordiem  Source code 
ordiem  Source code 
pej  Source code 
pejp1_ej  Source code 
pejp1_yjej  Source code 
pejp1zj1_ej  Source code 
pejp1zj1_yjej  Source code 
pyj_ej  Source code 
Files  

DESCRIPTION
 
NAMESPACE
 
R
 
R/ordinalclustering.R  
data
 
data/AERS.rda
 
man
 
man/AERS.Rd  
man/BOSpackage.Rd  
man/clustMultiBOS.Rd 
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